Version: 0.0.2

Author: Marcus Jacobson

License: MIT

Repository: GitHub

Project Status

  • Week 0: ✅ COMPLETE
  • Week 1: ✅ COMPLETE
  • Week 2: Not Started
  • Week 3: Not Started
  • Week 4: Not Started
  • Week 5: Not Started
  • Week 6: Not Started
  • Week 7: Not Started
  • Week 8: Not Started
  • Week 9: Not Started

⚠️ Important Project Update: This project has been restructured from a 12-week to a 9-week focused learning path based on lessons learned during Week 1. The new structure provides a more logical progression and realistic time investment for working professionals.

Project Goal

This article serves as an introduction to a comprehensive 9-week AI skilling roadmap focused on developing expertise in AI-infused security solutions using Microsoft technologies. This project combines hands-on learning with practical implementation across Microsoft Security Copilot, Defender XDR, Purview, Fabric, and Azure AI services while building a curated prompt library for security and governance scenarios.

The project has been optimized for working professionals with a logical progression through 4 distinct phases, designed for 8-12 hours per week (manageable with full-time work).

🌍 Regional Deployment Guidance: This project deploys infrastructure to East US region for complete AI security coverage and curriculum compliance, ensuring all advanced security features are available for hands-on learning.

As the project resources are published, the references will be linked below.

Project Outcomes

  • Comprehensive Prompt Library: A well-organized collection of AI prompts for security operations, governance, and AI agent scenarios
  • Hugo-based Documentation Site: Complete project documentation and findings published via GitHub Pages
  • Hands-on Experience: Practical deployment and configuration experience across the Microsoft security and AI stack
  • Customer-Ready Solutioning Skills: Framework and toolkit for AI-first security solution architecture and delivery
  • Secure AI Deployment Guide: End-to-end guide for deploying Microsoft 365 Copilot with security controls
  • Reusable AI Agent Toolkit: Custom AI agent built with Copilot Studio or Azure AI Foundry

Features

9-Week Learning Path Structure

The roadmap is organized into 4 distinct phases for optimal skill building:

Phase 1: Security Infrastructure Foundations (Weeks 1-3)

  • Week 1: Defender for Cloud Deployment Mastery - Master Defender for Cloud deployment with modern unified security operations foundation
  • Week 2: AI Integration & Enhanced Security Operations - Implement AI integration and enhanced security operations platform
  • Week 3: Defender XDR + Security Copilot Integration - Deploy advanced XDR + Security Copilot integration

Phase 2: Data Governance & Analytics (Weeks 4-5)

  • Week 4: Microsoft Purview for Data Governance - Comprehensive data governance implementation
  • Week 5: Microsoft Priva and Responsible AI - Responsible AI governance frameworks

Phase 3: Advanced Analytics & AI Development (Weeks 6-7)

  • Week 6: Microsoft Fabric for Secure Analytics - Secure analytics and data pipelines
  • Week 7: Azure AI Foundry & Secure AI Workloads - Secure AI workload deployment

Phase 4: Applied AI & Enterprise Delivery (Weeks 8-9)

  • Week 8: Copilot Studio for Security Agents - Security agents and AI automation
  • Week 9: Secure Copilot Deployment & Delivery Practices - Comprehensive delivery practices

Key Benefits of This Structure

  • Realistic Time Investment: Each week designed for 8-12 hours total (manageable with full-time work)
  • Logical Learning Flow: Each phase builds methodically on previous knowledge
  • Balanced Workload: Complex deployment work separated from AI integration
  • Practical Outcomes: Every week delivers deployable solutions and reusable assets
  • Enterprise Ready: Progresses from foundational skills to customer-facing delivery capability

Deliverables

  • Organized Prompt Library: Domain-specific categorization (Security, Governance, AI Agents) with weekly contributions
  • Weekly Learning Documentation: Blog posts documenting findings and learnings for each phase
  • Reference Architectures: Secure AI deployment patterns and best practices
  • Customer Solutioning Playbooks: Reusable prompts and frameworks for enterprise delivery
  • Deployment Automation: Infrastructure as Code templates and deployment guides
  • Regional Deployment Guide: East US specific configuration for complete AI security coverage

Repository Structure

The project is organized as a modular structure to support focused development:

Azure Ai Security Skills Challenge/
├── 00 - Project Setup & Admin/
├── 01 - Defender for Cloud Deployment Mastery/
├── 02 - AI Integration & Enhanced Security Operations/
├── 03 - Defender XDR + Security Copilot Integration/
├── 04 - Microsoft Purview for Data Governance/
├── 05 - Microsoft Priva and Responsible AI/
├── 06 - Microsoft Fabric for Secure Analytics/
├── 07 - Azure AI Foundry & Secure AI Workloads/
├── 08 - Copilot Studio for Security Agents/
├── 09 - Secure Copilot Deployment & Delivery Practices/
├── Prompt-Library/
├── reports/
└── Documentation and style guides

This skills challenge has inspired and informed several practical automation frameworks:

Usage

This project serves as both a personal skilling journey and a resource for others interested in AI-infused security solutions. The structured 9-week approach allows for progressive skill building while creating reusable assets for future customer engagements and team enablement.

The project is optimized for working professionals with each week designed for 8-12 hours of hands-on learning, making it manageable alongside full-time work commitments. Each phase builds methodically on previous knowledge while delivering practical, deployable solutions.

Key Learning Outcomes:

  • Phase 1: Master foundational security infrastructure and unified operations
  • Phase 2: Implement comprehensive data governance and responsible AI frameworks
  • Phase 3: Deploy advanced analytics and secure AI workloads
  • Phase 4: Build customer-ready solutions and delivery capabilities

Contributing

I welcome your feedback and contributions to improve this project. To provide feedback or ask questions, please use GitHub Discussions.

Thank you for your contributions and feedback!

License

I distribute my projects under the MIT Open Source license. You are welcome to re-use any of these projects for your own personal deployments, though I ask they are not used directly for any for-profit initiatives.

Additional Resources

For specific project details, please visit the Azure AI Security Skills Challenge repository.

To see my other projects, please visit the root of my Projects repository.